Journal ArticleDOI
Fuzzy C-Means Clustering Validity Function Based on Multiple Clustering Performance Evaluation Components
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This article is published in International Journal of Fuzzy Systems.The article was published on 2022-02-21. It has received 7 citations till now. The article focuses on the topics: Computer science & Cluster analysis.read more
Citations
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Journal ArticleDOI
A Method of Selecting Optimal Control Nodes for WSNs Based on C-Means Clustering Algorithm
Na Fang,Xiao-jing Wang +1 more
TL;DR: A method of selecting optimal control nodes for WSNs based on the C-means clustering algorithm (CCA) is proposed, which effectively prolongs the lifetime of WSN and improves the overall network output including throughput, energy consumption rate, and data transmission rate.
Journal ArticleDOI
Component-wise design method of fuzzy C-means clustering validity function based on CRITIC combination weighting
Journal ArticleDOI
Robust interval type-2 kernel-based possibilistic fuzzy clustering algorithm incorporating local and non-local information
Chengmao Wu,Si-jun Peng +1 more
TL;DR: Wang et al. as discussed by the authors presented a single fuzzifier interval type-2 kernel-based possibilistic fuzzy local and non-local information c-means clustering, and it is driven by deep neighborhood information for image segmentation in the presence of high noise.
Journal ArticleDOI
Exponent and Logarithm Component-Wise Construction Method of FCM Clustering Validity Function Based on Subjective and Objective Weighting
Proceedings ArticleDOI
Research on Online Reading User Clustering Method and Application based on FCM Algorithm
TL;DR: Zhang et al. as discussed by the authors analyzed the characteristics of all kinds of readers and made corresponding recommendations according to different readers and users, and put forward corresponding promotion countermeasures, so as to improve users' online reading satisfaction and the use frequency of online reading platform.
References
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Journal ArticleDOI
FCM: The fuzzy c-means clustering algorithm
TL;DR: A FORTRAN-IV coding of the fuzzy c -means (FCM) clustering program is transmitted, which generates fuzzy partitions and prototypes for any set of numerical data.
Journal ArticleDOI
A validity measure for fuzzy clustering
X.L. Xie,Gerardo Beni +1 more
TL;DR: The authors present a fuzzy validity criterion based on a validity function which identifies compact and separate fuzzy c-partitions without assumptions as to the number of substructures inherent in the data.
Journal ArticleDOI
A new approach to clustering
TL;DR: A new method of representation of the reduced data, based on the idea of “fuzzy sets,” is proposed to avoid some of the problems of current clustering procedures and to provide better insight into the structure of the original data.
Journal ArticleDOI
Some new indexes of cluster validity
James C. Bezdek,Nikhil R. Pal +1 more
TL;DR: This work reviews two clustering algorithms and three indexes of crisp cluster validity and shows that while Dunn's original index has operational flaws, the concept it embodies provides a rich paradigm for validation of partitions that have cloud-like clusters.